DisCoveR: Process Mining for Knowledge-Intensive Processes with DCR Graphs
Publikation: Bidrag til tidsskrift › Konferenceartikel › Forskning › fagfællebedømt
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Constraint-based notations aim to model processes by capturing their underlying rules instead of a limited number of potential process flows, leaving maximum flexibility for the actor to choose the best-suited order of execution for a particular process instance. Dynamic Condition Response (DCR) graphs are a constraint-based notation that has seen significant industrial adoption. In recent years there have been made significant inroads into the development of process mining algorithms and techniques for DCR Graphs. In this paper, accompanying the keynote of the same name delivered at the workshop Algorithms & Theories for the Analysis of Event Data, we discuss some of these recent advances in process mining with DCR Graphs and conclude by identifying a number of open challenges for DCR-based process mining.
|Tidsskrift||CEUR Workshop Proceedings|
|Status||Udgivet - 2023|
|Begivenhed||2023 Joint of the Workshop on Algorithms and Theories for the Analysis of Event Data and the International Workshop on Petri Nets for Twin Transition, ATAED and PN4TT 2023 - Caparica, Portugal|
Varighed: 25 jun. 2023 → 30 jun. 2023
|Konference||2023 Joint of the Workshop on Algorithms and Theories for the Analysis of Event Data and the International Workshop on Petri Nets for Twin Transition, ATAED and PN4TT 2023|
|Periode||25/06/2023 → 30/06/2023|
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